Anomalous pixel processing using adaptive decision-based filter systems and methods

Abstract

Techniques are provided to detect and/or replace anomalous pixels. In one example, a method includes receiving an image frame comprising a plurality of pixels having associated pixel values. The method also includes selecting a kernel of the pixels comprising a center pixel and a plurality of neighbor pixels. The method also includes, if the center pixel value exhibits an anomalous pixel condition, calculating a replacement pixel value using a gradient associated with at least a subset of pixel values of the neighbor pixels. Additional methods and systems are also provided.

What is claimed is: 
     
         1 . A method comprising:
 receiving an image frame comprising a plurality of pixels having associated pixel values;   selecting a kernel of the pixels comprising a center pixel and a plurality of neighbor pixels; and   if the center pixel value exhibits an anomalous pixel condition, calculating a replacement pixel value using a gradient associated with at least a subset of pixel values of the neighbor pixels.   
     
     
         2 . The method of  claim 1 , wherein the gradient is a smallest gradient associated with pixel values of second order neighbor pixels of the kernel. 
     
     
         3 . The method of  claim 1 , wherein:
 the anomalous pixel condition is a first anomalous pixel condition;   the replacement pixel value is a first replacement pixel value and an average of the subset of pixel values; and   if the center pixel value exhibits a second anomalous pixel condition, calculating a second replacement pixel value using a median pixel value of the kernel.   
     
     
         4 . The method of  claim 3 , wherein:
 the first anomalous pixel condition is an anomalous high pixel value; and   the second anomalous pixel condition is an anomalous low pixel value.   
     
     
         5 . The method of  claim 1 , wherein the subset is a subset of pixel values associated with second order neighbor pixels of the kernel and excludes pixel values of first order neighbor pixels of the kernel. 
     
     
         6 . The method of  claim 1 , further comprising:
 sorting the pixel values of the kernel;   selecting a pixel value limit from the sorted pixel values; and   comparing the center pixel value with the pixel value limit to detect the anomalous pixel condition.   
     
     
         7 . The method of  claim 1 , further comprising:
 calculating a difference between the center pixel value and a median pixel value of the kernel;   comparing the difference with a threshold to detect the anomalous pixel condition; and   adjusting the threshold in response to a number of the pixel values replaced in the image frame.   
     
     
         8 . The method of  claim 1 , wherein the calculating the replacement pixel value further comprises adding an offset to compensate for cross-talk among the center pixel and one or more of the neighbor pixels. 
     
     
         9 . The method of  claim 1 , further comprising:
 performing the selecting and the calculating for a plurality of kernels of the image frame;   replacing the center pixel values of the kernels with the replacement pixel values to provide a processed image frame; and   repeating the selecting and the calculating for a plurality of kernels of the processed image frame.   
     
     
         10 . The method of  claim 1 , wherein:
 the image frame is a thermal image frame; and   the kernel is a 3 pixel by 3 pixel kernel.   
     
     
         11 . A system comprising:
 a logic device configured to:
 receive an image frame comprising a plurality of pixels having associated pixel values; 
 select a kernel of the pixels comprising a center pixel and a plurality of neighbor pixels; and 
 if the center pixel value exhibits an anomalous pixel condition, calculate a replacement pixel value using a gradient associated with at least a subset of pixel values of the neighbor pixels. 
   
     
     
         12 . The system of  claim 11 , wherein the gradient is a smallest gradient associated with pixel values of second order neighbor pixels of the kernel. 
     
     
         13 . The system of  claim 11 , wherein:
 the anomalous pixel condition is a first anomalous pixel condition;   the replacement pixel value is a first replacement pixel value and an average of the subset of pixel values; and   the logic device is configured to calculate a second replacement pixel value using a median pixel value of the kernel if the center pixel value exhibits a second anomalous pixel condition.   
     
     
         14 . The system of  claim 13 , wherein:
 the first anomalous pixel condition is an anomalous high pixel value; and   the second anomalous pixel condition is an anomalous low pixel value.   
     
     
         15 . The system of  claim 11 , wherein the subset is a subset of pixel values associated with second order neighbor pixels of the kernel and excludes pixel values of first order neighbor pixels of the kernel. 
     
     
         16 . The system of  claim 11 , wherein the logic device is configured to:
 sort the pixel values of the kernel;   select a pixel value limit from the sorted pixel values; and   compare the center pixel value with the pixel value limit to detect the anomalous pixel condition.   
     
     
         17 . The system of  claim 11 , wherein the logic device is configured to:
 calculate a difference between the center pixel value and a median pixel value of the kernel;   compare the difference with a threshold to detect the anomalous pixel condition; and   adjust the threshold in response to a number of the pixel values replaced in the image frame.   
     
     
         18 . The system of  claim 11 , wherein the logic device is configured to add an offset to the replacement pixel value to compensate for cross-talk among the center pixel and one or more of the neighbor pixels. 
     
     
         19 . The system of  claim 11 , wherein the logic device is configured to:
 performing the select and the calculate for a plurality of kernels of the image frame;   replace the center pixel values of the kernels with the replacement pixel values to provide a processed image frame; and   repeat the select and the calculate for a plurality of kernels of the processed image frame.   
     
     
         20 . The system of  claim 11 , further comprising:
 a thermal imager configured to capture the image frame;   wherein the image frame is a thermal image frame; and   wherein the kernel is a 3 pixel by 3 pixel kernel.